Despite the dual role for TGF-beta as both tumor suppressor and tumor promoter in carcinogenesis, preclinical data from our lab and others has previously suggested that strategies to antagonize TGF-beta may selectively reduce the undesirable tumor promoting effects of this growth factor while sparing the desirable effects on tumor suppression and normal homeostasis. Based on these promising preclinical results, an anti-TGF-beta antibody is in early phase clinical trials for the treatment of advanced cancer (NCI-06-C-0200). However, given the complex biology of TGF-beta, the successful development of TGF-beta antagonists for cancer therapy will depend on a clear understanding of how these agents work, and the related question of how to select patients who will benefit from this type of treatment. Our major focus in FY11 has been to establish a panel of transplantable syngeneic mouse models of metastatic breast cancer, assess the therapeutic effects of anti-TGF-beta antibodies in the different models and then use the panel to develop predictive biomarkers of response to anti-TGF-beta therapy. We have assembled a panel of 11 metastatic mammary models derived from spontaneous or genetically engineered mouse mammary tumors that can be transplanted into immunocompetent mouse hosts. A range of tumor histologies and mouse strain background are represented. We have successfully assessed the effect of a pan-TGF-beta neutralizing mouse monoclonal antibody on metastasis (1D11) in 9 of the models, and we find that while 1D11 inhibits metastasis in some models, it has no effect or can even stimulate metastasis in other models. Using this panel, we have assessed the predictive power of a number of plausible candidate biomarkers. We have found that therapeutic response to TGF-beta antagonism is not successfully predicted by (a) TGF-beta expression levels in the tumor cells, (b) loss of growth inhibitory response of the tumor cells to TGF-beta, (c) Six-1 expression levels, (d) Claudin-low status, (e) activation of non-canonical TGF-beta signaling pathways. We are now proceeding with discovery-based approaches to the identification of predictive biomarkers, including testing gene signatures of TGF-beta-mediated tumor suppression that we identified in the related project ZIA BC 005785. We have also examined mechanisms underlying the undesirable stimulation of metastasis by 1D11 in some models, and we have shown that unlike the therapeutic effect, this stimulatory effect is not dependent on the presence of an adaptive immune response.